maximum of two exponential random variables

Plots a line instead of a colormap. This is a remarkable theorem known as Fouriers theorem. Deep learning is a part of artificial intelligence that makes computers learn from data. This is where our friend Fourier comes in. Syntax: matplotlib.pyplot.specgram(x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, cmap=None, xextent=None, pad_to=None, sides=None, scale_by_freq=None, mode=None, scale=None, vmin=None, vmax=None, *, data=None, **kwargs). Voila! Thats it! is not supported. 'magnitude' returns the magnitude Its default value is 2. window: This parameter take a data segment as an argument and return the windowed version of the segment. I mean how to use subplot command and how to store each figure in loop. What is the use of NTP server when devices have accurate time? | 7 Practical Python Applications, Python Programming Foundation -Self Paced Course, Complete Interview Preparation- Self Paced Course, Data Structures & Algorithms- Self Paced Course. Support Matplotlib. The Mel Spectrogram is the result of the following pipeline: Separate to windows: Sample the input with windows of size n_fft=2048, making hops of size hop_length=512 each time to sample the next window. If a spectrogram input S is provided, then it is mapped directly onto the mel basis by mel_f.dot (S). Traditional English pronunciation of "dives"? in this example: matplotlib.axes.Axes.specgram / matplotlib.pyplot.specgram, Total running time of the script: ( 0 minutes 1.161 seconds), Download Python source code: specgram_demo.py, Download Jupyter notebook: specgram_demo.ipynb. This should NOT be used to get zero padding, or the For example, we can easily tell the difference between 500 and 1000 Hz, but we will hardly be able to tell a difference between 10,000 and 10,500 Hz, even though the distance between the two pairs are the same. This corresponds to is not appropriate to use. # The `specgram` method returns 4 objects. When you compute the mel spectrogram using librosa.feature.melspectrogram (y=y, sr=sr) you implicitly create a mel filter using the parameters fmin=0 and fmax=sr/2 (see docs here ). Deep learning is a part of artificial intelligence that makes computers learn from data. The windowing function window is applied to each segment, and the amount of overlap of each segment is specified with noverlap. to download the full example code. matplotlib mel spectrogram. Does subclassing int to forbid negative integers break Liskov Substitution Principle? The fast Fourier transform is a powerful tool that allows us to analyze the frequency content of a signal, but what if our signals frequency content varies over time? A single spectrum, similar to having a single segment when mode is 'magnitude'. Ok. We are almost there! Well, not quite, but I hope this post made the mel spectrogram a little less intimidating. Generate a Mel scale: Take the entire . plt. In 1937, Stevens, Volkmann, and Newmann proposed a unit of pitch such that equal distances in pitch sounded equally distant to the listener. I have a folder containing multiple wav files (currently say 4). 'phase' returns the phase spectrum with unwrapping. Note that for noverlap>0 the width This can have following values : 'default', 'onesided' and 'twosided'. # import the libraries. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, path=glob.glob('E://*.wav') for i in range(0,13): for p in path: y, sr = librosa.load(p, sr=16000) mfcc=librosa.feature.mfcc(y) S = librosa.feature.melspectrogram(y, sr) #fig, ax = plt.subplot() librosa.display.waveplot(y, sr=sr) plt.subplot(12/3,12/4,i+1) librosa.display.specshow(mfcc, x_axis="time",y_axis="mel") plt.subplot(12/3,12/4,i+2) librosa.display.specshow(librosa.power_to_db(S)) plt.subplot(12/3,12/4,i+3). Return Variable Number Of Attributes From XML As Comma Separated Values. What we have captured is a waveform for the signal, and this can be interpreted, modified, and analyzed with computer software. specified with noverlap. matplotlib mel spectrogram matplotlib mel spectrogram. librosa.display.specshow(mel_spect, y_axis='mel', fmax=8000, x_axis='time'); We took samples of air pressure over time to digitally represent an audio, We mapped the audio signal from the time domain to the frequency domain using the, We converted the y-axis (frequency) to a log scale and the color dimension (amplitude) to decibels to form the, We mapped the y-axis (frequency) onto the. Compute and plot a spectrogram of data in x. There is also a phenomenal video by 3Blue1Brown on the Fourier Transform if you would like to learn more here. I just use one more line, after defining figure specification and its done: [axi.set_axis_off() for axi in ax.ravel()] Also yOu can follow this link. How do I set the figure title and axes labels font size? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Please guide. We have a digital representation of an audio signal that we can work with. My profession is written "Unemployed" on my passport. The windowing function window is applied to each Is this homebrew Nystul's Magic Mask spell balanced? frequencies = np.arange (5,105,5) this is dB power (10 * log10). I will use this algorithm on a windowed segment of our example audio. 'linear' calls detrend_linear. We perform a mathematical operation on frequencies to convert them to the mel scale. Studies have shown that humans do not perceive frequencies on a linear scale. We'll use the peak power as reference. With only a couple lines of code, we have created a spectrogram. At the end of the day though, I found out that Mel wasnt so standoffish. Find out here! MATLAB compatibility. The default is None, numpy.bartlett, scipy.signal, scipy.signal.get_window, etc. A mel spectrogram is a spectrogram where the frequencies are converted to the mel scale. The mlab Or not? # Define the list of frequencies. Differs in the default overlap; in returning the mean of the segment periodograms; in not returning times; and in generating a line plot instead of colormap. Do you know how to plot just 1 spectrogram? Below examples illustrate the matplotlib.pyplot.specgram() function in matplotlib.pyplot: Writing code in comment? Since I don't have the spectrogram files I've used randomly created NumPy arrays. Plots a line instead of a colormap. First impressions about Ubers Ludwig. Stack Overflow for Teams is moving to its own domain! scaling of the result will be incorrect; use pad_to for this instead. I am not able to plot the graph, only extracted the features. How to change the figure size of a seaborn axes or figure level plot. Both are supported by librosa, as we'll show here. Whether the resulting density values should be scaled by the scaling Compute and plot a spectrogram of data in x.Data are split into NFFT length segments and the . 'mean' calls of the bins is smaller than those of the segments. window_hanning, window_none, numpy.blackman, numpy.hamming, That was a lot of information to take in, especially if you are new to signal processing like myself. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. The function applied to each segment before fft-ing, designed to remove How does it do? Download Jupyter notebook: specgram_demo.ipynb. Right after librosa.display.specshow(librosa.power_to_db(S), x_axis='time', y_axis='log', ax=ax[i, 2]) # spectrogram in row i, column 2 line at the end of the for loop. Fs : This parameter is a scalar. How do we capture this information digitally? but you can use a custom function as well. In my figure, it works. (Default: 16000) n_fft ( int, optional) - Size of FFT, creates n_fft // 2 + 1 bins. matplotlib.pyplot.specgram matplotlib.pyplot.specgram (x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, cmap=None, xextent=None, pad_to=None, sides=None, scale_by_freq=None, mode=None, scale=None, vmin=None, vmax=None, *, data=None, **kwargs) [source] Plot a spectrogram. When taking samples of the signal over time, we only capture the resulting amplitudes. We have a solid grasp on the spectrogram part, but what about Mel. Who is he? power spectral density. Whats amazing is that after going through all those mental gymnastics to try to understand the mel spectrogram, it can be implemented in only a couple lines of code. figure ( figsize= ( 12, 4 )) # Display the spectrogram on a mel scale. more points in the plot, allowing for more detail. (20 * log10). Replace first 7 lines of one file with content of another file. Plots a line instead of a colormap. A simple machine learning tool. torchaudio.transforms module contains common audio processings and feature extractions. If you're familiar with matplotlib already, you may know that there are two ways of using it: the pyplot interface and the object-oriented interface. # Fixing random state for reproducibility. If you just want to display picturesYou just need to add a line of code plt.show () import os import matplotlib matplotlib.use ('Agg') # No pictures displayed import pylab import librosa import librosa.display import numpy as np sig, fs = librosa.load ('path_to_my_wav_file') # make pictures name save_path = 'test.jpg' pylab.axis ('off . A planet you can take off from, but never land back. NFFT length segments and the spectrum of each section is linspace(1, 6, math. I know, right? Click here spectrum (the minimum distance between resolvable peaks), this can give The spectrogram is plotted as a colormap (using imshow). When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com. MelSpectrogram. Compute and plot a spectrogram of data in x. Matplotlib is a community project maintained for and by its users You can help by answering questions on discourse, reporting a bug or requesting a feature on GitHub, or improving the documentation and code! Will it have a bad influence on getting a student visa? It is used to calculate log-power Mel spectrogram. The use of the following functions, methods, classes and modules is shown To learn more, see our tips on writing great answers. music_data,rate = librosa.load(music) arr= librosa.feature.melspectrogram(music_data,sr=rate,n_fft=2048,hop_length=512,n_mels=128) log_spec = librosa.power_to_db(arr . generate link and share the link here. The parameters detrend and scale_by_freq do only apply when mode This is called the mel scale. import numpy as np. Find centralized, trusted content and collaborate around the technologies you use most. computed. done using : [axi.set_axis_off() for axi in ax.ravel()], can someone plz tell me how to remove the axis from all these plots? It looks like a jumbled mess. I want to plot the wav, its mfcc and mel spectrogram in a row , so finally a figure with 12 plots(each row with three figure, and hence four rows). That was a lot of information to take in, especially if you are new to signal processing like me. Data are split into function is passed as the argument, it must take a data segment as an sample_rate ( int, optional) - Sample rate of audio signal. Example: The Python example program below first displays the signal in time domain. which sets pad_to equal to NFFT. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. most efficient. interpreted as data[s] (unless this raises an exception): Additional keyword arguments are passed on to imshow Data are split into NFFT length segments and the spectrum of each section is computed. Yes sir did that only. Here, we are going to discuss how to utilize the function plt.specgram () to draw the spectrogram in Python. 'default' is 'dB' if mode is 'psd' or GitHub - swharden/Spectrogram: .NET library for creating . rev2022.11.7.43014. detrend_mean. ceil(6 / Time_diff)) This is possible because every signal can be decomposed into a set of sine and cosine waves that add up to the original signal. A single spectrum, similar to having a single segment when mode is 'phase'. Check your email for updates. Otherwise this is dB amplitude However, if you continue to review the concepts laid out in this post (and spend enough time staring at the corner of a wall thinking about them), itll begin to make sense! The number of data points used in each block for the FFT. log_S = librosa. This is exactly what is done, and it is called the short-time Fourier transform. Also I am not getting how to set this outer loop i, which is I think the number of plots. Thanks for contributing an answer to Stack Overflow! librosa.display.specshow(spec, sr=sr, x_axis='time', y_axis='log'); mel_spect = librosa.feature.melspectrogram(y=y, sr=sr, n_fft=2048, hop_length=1024). integration over the returned frequency values. I hope this short post will clarify some of the confusion and explain the mel spectrogram from the ground up. When mode is 'psd', librosa.feature.melspectrogram. The following diagram shows the relationship between some of the available transforms. The spectrogram is plotted as a colormap To create window vectors see the FFT. 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Important differences between Python 2.x and Python 3.x with examples, Reading Python File-Like Objects from C | Python. Time_Arr = np. Have you put the plt.axis('off') at the end of the for a loop. The default is True for is set to 'psd'. Light bulb as limit, to what is current limited to? Theres a lot going on here. cz shadow 2 orange videos; post translational modification notes; Newsletters; nissan murano 2022; homestead exemption laws of wyoming; lionel 675 parts Join us on Discourse Join us on GitHub; Cite import math. A single spectrum, similar to having a single segment when mode is 'angle'. Please use ide.geeksforgeeks.org, Publi par 19 novembre 2021 idea gear indicator honda sur matplotlib mel spectrogram. choose one of the functions: 'none' calls detrend_none. I think I've found a bug, and if this is a mess up on my part, I . However, if you continue to review the concepts laid out in this post (and spend enough time staring at the corner of a wall thinking about them), it'll begin to make sense! For audio, the quantity that varies is air pressure. November 18, 2021 . The times corresponding to midpoints of segments (i.e., the columns 'angle' returns the phase spectrum without unwrapping. Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. If you would like to see a cool application of this topic, check out my post on musical genre classification where I use mel spectrograms to train a convolutional neural network to predict the genre of a song. The fast Fourier transform (FFT) is an algorithm that can efficiently compute the Fourier transform. A signal is a variation in a certain quantity over time. You can think of a spectrogram as a bunch of FFTs stacked on top of each other. You may be wondering though, how do we extract useful information from this? GeeksforGeeks Python Foundation Course - Learn Python in Hindi! Wow! It is widely used in signal processing. Could you plz see the code snippet and tell me exactly where I should write this. A good visual is in order. Click here if you want a good intuition for why this theorems is true. data and two-sided for complex data. Unlike in MATLAB, where the detrend parameter # sample rate and hop length parameters are used to render the time axis. frequency, which gives density in units of 1/Hz. I will use this algorithm on a windowed segment of our . Transforms are implemented using torch.nn.Module. Sounds easy, right? Asking for help, clarification, or responding to other answers. Not the answer you're looking for? (How) can I apply the seaborn despine function to individual subplots? The center frequency of x, which offsets the x extents of the By using our site, you Python | Index of Non-Zero elements in Python list, Python - Read blob object in python using wand library, Python | PRAW - Python Reddit API Wrapper, twitter-text-python (ttp) module - Python, Reusable piece of python functionality for wrapping arbitrary blocks of code : Python Context Managers, Python program to check if the list contains three consecutive common numbers in Python, Creating and updating PowerPoint Presentations in Python using python - pptx, Filter Python list by Predicate in Python, Python | Set 4 (Dictionary, Keywords in Python), Python program to build flashcard using class in Python. If given, the following parameters also accept a string s, which is When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com.. Create MelSpectrogram for a raw audio signal. While not increasing the actual resolution of the Python | Sort Python Dictionaries by Key or Value, What is Python Used For? How to set a single, main title above all the subplots with Pyplot? The image extent along the x-axis. Making statements based on opinion; back them up with references or personal experience. argument and return the windowed version of the segment. These signals are known as non periodic signals. Common ways to build a processing pipeline are to define custom Module class or chain Modules together using torch.nn . logamplitude ( S, ref_power=np. Parameters: This method accept the following parameters that are described below: The resultant is (spectrum, freqs, t, im). module defines detrend_none, detrend_mean, and detrend_linear, I dont know how to make it look like a code here in comments? which makes the specgram image. import matplotlib.pyplot as plot. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. x: This parameter is a sequence of data. The rate at which we sample the data can vary, but is most commonly 44.1kHz, or 44,100 samples per second. We need a way to represent the spectrum of these signals as they vary over time. and then filtered and downsampled to baseband. MATLAB - Add legend next to some chosen plots in a subplot - for loop. Stack Overflow for Teams is moving to its own domain! pyplot as plt. What sort of spectrum to use. Which sides of the spectrum to return. import numpy as np. Total running time of the script: ( 0 minutes 1.161 seconds) Download Python source code: specgram_demo.py. This is because humans can only perceive a very small and concentrated range of frequencies and amplitudes. The specgram() function in pyplot module of matplotlib library is used to plot a spectrogram. Compute a mel-scaled spectrogram. How to plot the sound wave, mfcc,and mel spectrogram on a single figure? Default is 'psd', which takes the Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. The program also displays the signal in frequency domain using the spectrogram. Cross Validation - What, Why and How | Machine Learning, y, sr = librosa.load('./example_data/blues.00000.wav'), spec = np.abs(librosa.stft(y, hop_length=512)). There are some additional details going on behind the scenes when computing the spectrogram. stackoverflow.com/questions/25862026/turn-off-axes-in-subplots, Stop requiring only one assertion per unit test: Multiple assertions are fine, Going from engineer to entrepreneur takes more than just good code (Ep. We can take samples of the air pressure over time. if mode is 'angle' or 'phase'. Calculations are simple with Python , and expression syntax is straightforward: the operators. import matplotlib. Connect and share knowledge within a single location that is structured and easy to search. A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. A function or a vector of length NFFT. In Summary. You may be thinking, hey, cant we compute several spectrums by performing FFT on several windowed segments of the signal? Yes! Can plants use Light from Aurora Borealis to Photosynthesize? The default sets xmin to the It is widely used in signal processing. How to print the current filename with a function defined in another file? log-power Mel spectrogram. How can you prove that a certain file was downloaded from a certain website? 'dB' returns the values in dB scale. The Fourier transform is a mathematical formula that allows us to decompose a signal into its individual frequencies and the frequencys amplitude. spectrum. You can also use a string to Matplotlib is a library in Python and it is numerical mathematical extension for NumPy library. 'magnitude' and 'linear' otherwise. Such is the case with most audio signals such as music and speech. It took me quite a while to understand it. I think for subplots() it wont work. The number of points to which the data segment is padded when performing It is a way to visually represent a signals loudness, or amplitude, as it varies over time at different frequencies. Do we still need PCR test / covid vax for travel to . (AKA - how up-to-date is travel info)? Can some one help with this for loop please. If a time-series input y, sr is provided, then its magnitude spectrogram S is first computed, and then mapped onto the mel scale by mel_f.dot (S**power). So I need 4X3Xi matrix of 12 plots. This is great! You just need to change imshow with desired plottings. Concealing One's Identity from the Public When Purchasing a Home, Execution plan - reading more records than in table. one-sided spectrum, while 'twosided' forces two-sided. Who wouldve thought? 1. The result is called a spectrum. 'onesided' forces the return of a What Are RBMs, Deep Belief Networks and Why Are They Important to Deep Learning? JavaScript vs Python : Can Python Overtop JavaScript by 2020? the mean or linear trend. Thats a lot to take in. The y-axis is converted to a log scale, and the color dimension is converted to decibels (you can think of this as the log scale of the amplitude). The use of the following functions, methods, classes and modules is shown in this example: matplotlib.axes.Axes.specgram / matplotlib.pyplot.specgram. First, the pyplot interface: plt.figure() librosa.display.specshow(S_db) plt.colorbar() And now the object-oriented interface. is a vector, in Matplotlib it is a function. This can be different from NFFT, which specifies the number This is a composition of torchaudio.transforms.Spectrogram () and and torchaudio.transforms.MelScale (). Fig and axs returns in the function plt.subplots not plt.subplot.You can also use that method but outside of the for loop and then access the axs elements. 'default' is one-sided for real An audio signal is comprised of several single-frequency sound waves. max) # Make a new figure. This must be 'linear' A power 2 is In other words, it converts the signal from the time domain into the frequency domain. The scaling of the values in the spec. (using imshow). We are building the next-gen data science ecosystem https://www.analyticsvidhya.com, Data Storytelling | Math | Driven by Curiosity. This allows for I did that, just axis is creating problem , I tried axis(off) but not working for me. 'linear' is no scaling. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface. Its default value is window_hanning() sides: This parameter specifies which sides of the spectrum to return. {'default', 'onesided', 'twosided'}, optional, {'none', 'mean', 'linear'} or callable, default: 'none', {'default', 'psd', 'magnitude', 'angle', 'phase'}, Animated image using a precomputed list of images, matplotlib.animation.ImageMagickFileWriter, matplotlib.artist.Artist.format_cursor_data, matplotlib.artist.Artist.set_sketch_params, matplotlib.artist.Artist.get_sketch_params, matplotlib.artist.Artist.set_path_effects, matplotlib.artist.Artist.get_path_effects, matplotlib.artist.Artist.get_window_extent, matplotlib.artist.Artist.get_transformed_clip_path_and_affine, matplotlib.artist.Artist.is_transform_set, matplotlib.axes.Axes.get_legend_handles_labels, matplotlib.axes.Axes.get_xmajorticklabels, matplotlib.axes.Axes.get_xminorticklabels, matplotlib.axes.Axes.get_ymajorticklabels, matplotlib.axes.Axes.get_yminorticklabels, matplotlib.axes.Axes.get_rasterization_zorder, matplotlib.axes.Axes.set_rasterization_zorder, matplotlib.axes.Axes.get_xaxis_text1_transform, matplotlib.axes.Axes.get_xaxis_text2_transform, matplotlib.axes.Axes.get_yaxis_text1_transform, matplotlib.axes.Axes.get_yaxis_text2_transform, matplotlib.axes.Axes.get_default_bbox_extra_artists, matplotlib.axes.Axes.get_transformed_clip_path_and_affine, matplotlib.axis.Axis.remove_overlapping_locs, matplotlib.axis.Axis.get_remove_overlapping_locs, matplotlib.axis.Axis.set_remove_overlapping_locs, matplotlib.axis.Axis.get_ticklabel_extents, matplotlib.axis.YAxis.set_offset_position, matplotlib.axis.Axis.limit_range_for_scale, matplotlib.axis.Axis.set_default_intervals, matplotlib.colors.LinearSegmentedColormap, matplotlib.colors.get_named_colors_mapping, matplotlib.gridspec.GridSpecFromSubplotSpec, matplotlib.pyplot.install_repl_displayhook, matplotlib.pyplot.uninstall_repl_displayhook, matplotlib.pyplot.get_current_fig_manager, mpl_toolkits.mplot3d.art3d.Line3DCollection, mpl_toolkits.mplot3d.art3d.Patch3DCollection, mpl_toolkits.mplot3d.art3d.Path3DCollection, mpl_toolkits.mplot3d.art3d.Poly3DCollection, mpl_toolkits.mplot3d.art3d.get_dir_vector, mpl_toolkits.mplot3d.art3d.line_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.pathpatch_2d_to_3d, mpl_toolkits.mplot3d.art3d.poly_collection_2d_to_3d, mpl_toolkits.mplot3d.proj3d.inv_transform, mpl_toolkits.mplot3d.proj3d.persp_transformation, mpl_toolkits.mplot3d.proj3d.proj_trans_points, mpl_toolkits.mplot3d.proj3d.proj_transform, mpl_toolkits.mplot3d.proj3d.proj_transform_clip, mpl_toolkits.mplot3d.proj3d.view_transformation, mpl_toolkits.mplot3d.proj3d.world_transformation, mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDirectionArrows, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea, mpl_toolkits.axes_grid1.anchored_artists.AnchoredEllipse, mpl_toolkits.axes_grid1.anchored_artists.AnchoredSizeBar, mpl_toolkits.axes_grid1.axes_divider.AxesDivider, mpl_toolkits.axes_grid1.axes_divider.AxesLocator, mpl_toolkits.axes_grid1.axes_divider.Divider, mpl_toolkits.axes_grid1.axes_divider.HBoxDivider, mpl_toolkits.axes_grid1.axes_divider.SubplotDivider, mpl_toolkits.axes_grid1.axes_divider.VBoxDivider, mpl_toolkits.axes_grid1.axes_divider.make_axes_area_auto_adjustable, mpl_toolkits.axes_grid1.axes_divider.make_axes_locatable, mpl_toolkits.axes_grid1.axes_grid.AxesGrid, mpl_toolkits.axes_grid1.axes_grid.CbarAxes, mpl_toolkits.axes_grid1.axes_grid.CbarAxesBase, mpl_toolkits.axes_grid1.axes_grid.ImageGrid, mpl_toolkits.axes_grid1.axes_rgb.make_rgb_axes, mpl_toolkits.axes_grid1.axes_size.AddList, mpl_toolkits.axes_grid1.axes_size.Fraction, mpl_toolkits.axes_grid1.axes_size.GetExtentHelper, mpl_toolkits.axes_grid1.axes_size.MaxExtent, mpl_toolkits.axes_grid1.axes_size.MaxHeight, mpl_toolkits.axes_grid1.axes_size.MaxWidth, mpl_toolkits.axes_grid1.axes_size.Scalable, mpl_toolkits.axes_grid1.axes_size.SizeFromFunc, mpl_toolkits.axes_grid1.axes_size.from_any, mpl_toolkits.axes_grid1.inset_locator.AnchoredLocatorBase, mpl_toolkits.axes_grid1.inset_locator.AnchoredSizeLocator, mpl_toolkits.axes_grid1.inset_locator.AnchoredZoomLocator, mpl_toolkits.axes_grid1.inset_locator.BboxConnector, mpl_toolkits.axes_grid1.inset_locator.BboxConnectorPatch, mpl_toolkits.axes_grid1.inset_locator.BboxPatch, mpl_toolkits.axes_grid1.inset_locator.InsetPosition, mpl_toolkits.axes_grid1.inset_locator.inset_axes, mpl_toolkits.axes_grid1.inset_locator.mark_inset, mpl_toolkits.axes_grid1.inset_locator.zoomed_inset_axes, mpl_toolkits.axes_grid1.mpl_axes.SimpleAxisArtist, mpl_toolkits.axes_grid1.mpl_axes.SimpleChainedObjects, mpl_toolkits.axes_grid1.parasite_axes.HostAxes, mpl_toolkits.axes_grid1.parasite_axes.HostAxesBase, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxes, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxesBase, mpl_toolkits.axes_grid1.parasite_axes.host_axes, mpl_toolkits.axes_grid1.parasite_axes.host_axes_class_factory, mpl_toolkits.axes_grid1.parasite_axes.host_subplot, mpl_toolkits.axes_grid1.parasite_axes.host_subplot_class_factory, mpl_toolkits.axes_grid1.parasite_axes.parasite_axes_class_factory, mpl_toolkits.axisartist.angle_helper.ExtremeFinderCycle, mpl_toolkits.axisartist.angle_helper.FormatterDMS, mpl_toolkits.axisartist.angle_helper.FormatterHMS, mpl_toolkits.axisartist.angle_helper.LocatorBase, mpl_toolkits.axisartist.angle_helper.LocatorD, mpl_toolkits.axisartist.angle_helper.LocatorDM, mpl_toolkits.axisartist.angle_helper.LocatorDMS, mpl_toolkits.axisartist.angle_helper.LocatorH, mpl_toolkits.axisartist.angle_helper.LocatorHM, mpl_toolkits.axisartist.angle_helper.LocatorHMS, mpl_toolkits.axisartist.angle_helper.select_step, mpl_toolkits.axisartist.angle_helper.select_step24, mpl_toolkits.axisartist.angle_helper.select_step360, mpl_toolkits.axisartist.angle_helper.select_step_degree, mpl_toolkits.axisartist.angle_helper.select_step_hour, mpl_toolkits.axisartist.angle_helper.select_step_sub, mpl_toolkits.axisartist.axes_grid.AxesGrid, mpl_toolkits.axisartist.axes_grid.CbarAxes, mpl_toolkits.axisartist.axes_grid.ImageGrid, mpl_toolkits.axisartist.axis_artist.AttributeCopier, mpl_toolkits.axisartist.axis_artist.AxisArtist, mpl_toolkits.axisartist.axis_artist.AxisLabel, mpl_toolkits.axisartist.axis_artist.GridlinesCollection, mpl_toolkits.axisartist.axis_artist.LabelBase, mpl_toolkits.axisartist.axis_artist.TickLabels, mpl_toolkits.axisartist.axis_artist.Ticks, mpl_toolkits.axisartist.axisline_style.AxislineStyle, mpl_toolkits.axisartist.axislines.AxesZero, mpl_toolkits.axisartist.axislines.AxisArtistHelper, mpl_toolkits.axisartist.axislines.AxisArtistHelperRectlinear, mpl_toolkits.axisartist.axislines.GridHelperBase, mpl_toolkits.axisartist.axislines.GridHelperRectlinear, mpl_toolkits.axisartist.clip_path.clip_line_to_rect, mpl_toolkits.axisartist.floating_axes.ExtremeFinderFixed, mpl_toolkits.axisartist.floating_axes.FixedAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.FloatingAxes, mpl_toolkits.axisartist.floating_axes.FloatingAxesBase, mpl_toolkits.axisartist.floating_axes.FloatingAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.GridHelperCurveLinear, mpl_toolkits.axisartist.floating_axes.floatingaxes_class_factory, mpl_toolkits.axisartist.grid_finder.DictFormatter, mpl_toolkits.axisartist.grid_finder.ExtremeFinderSimple, mpl_toolkits.axisartist.grid_finder.FixedLocator, mpl_toolkits.axisartist.grid_finder.FormatterPrettyPrint, mpl_toolkits.axisartist.grid_finder.GridFinder, mpl_toolkits.axisartist.grid_finder.MaxNLocator, mpl_toolkits.axisartist.grid_helper_curvelinear, mpl_toolkits.axisartist.grid_helper_curvelinear.FixedAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.FloatingAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.GridHelperCurveLinear.
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